Hydrocarbons, such as oil and gas, are commonly obtained from subterranean formations. The development of subterranean operations and the processes involved in removing hydrocarbons from a subterranean formation are complex. Typically, subterranean operations involve a number of different steps such as, for example, drilling a wellbore at a desired well site, treating the wellbore to optimize production of hydrocarbons, and performing necessary steps to produce and process hydrocarbons from the subterranean formation.
Modern oil field operations demand a great quantity of information relating to the parameters and conditions encountered downhole. Such information may include characteristics of the earth formations traversed by the wellbore and data relating to the diameter and configuration of the wellbore itself. The collection of information relating to conditions downhole, which commonly is referred to as “logging,” can be performed by several methods, including wireline logging, measurement-while-drilling (MWD), logging-while-drilling (LWD), drillpipe conveyed logging, and coil tubing conveyed logging. A variety of logging tools are available for use with each of these methods. These logging tools may be used to perform wellbore imaging. Wellbore imaging is an important aspect of drilling and geosteering when performing subterranean operations.
One of the logging methods utilized to analyze a formation is acoustic logging. An acoustic logging tool may include an acoustic source (transmitter) and one or more receivers that may be spaced several inches or feet away from each other. An acoustic signal is transmitted by the acoustic source and received at the receivers of the acoustic tool which are spaced apart from the acoustic source. Measurements are repeated every few inches as the tool is drawn up (or down) the wellbore. The acoustic signal from the source travels through the formation adjacent the wellbore to the receiver array, and the arrival times and perhaps other characteristics of the receiver responses are recorded. Typically, compressional wave (P-wave), shear wave (S-wave), and Stoneley wave arrivals and waveforms are detected by the receivers and are processed. The processing of the data received is often accomplished uphole or may be handled in real-time in the tool itself. Regardless, the information that is recorded is typically used to determine formation characteristics such as formation slowness (the inverse of acoustic speed), from which pore pressure, porosity, and other formation property determinations can be made. In some tools, the acoustic signals may even be used to image the formation.
Different techniques may be used to process the received acoustic signals in order to obtain information regarding the formation characteristics. One of the methods used to determine compressional slowness is Slowness-Time Coherence (“STC”) processing. In STC processing, the measured signal is time window “filtered” and stacked, and a semblance function is computed. The semblance function relates the presence or absence of an arrival with a particular assumed slowness and particular assumed arrival time. If the assumed slowness and arrival time do not coincide with that of the measured arrival time, the semblance takes on a smaller value. As a result, arrivals of the received waveforms manifest themselves as local peaks in a plot of semblance versus slowness and arrival time.
Acoustic array processing is one of the methods used for estimating formation properties such as, for example, compressional and/or shear slowness, using an acoustic logging tool data. However, one of the major hurdles for estimating the formation properties is the natural phenomenon of dispersive wave propagation along the wellbore. The dispersive nature of wave propagation may vary depending on the type of source excitation used to generate the waves at the acoustic source, formation type, wellbore diameter, etc. Specifically, the source of excitation may be, for example, a monopole, a dipole, or a quadrupole source. In fact, due to the dispersive nature of wave propagation, the true shear formation slowness estimation remains complicated even when utilizing advanced array processing, such as point-to-point time domain coherence analysis. Typical prior art systems estimate the slowness of the formation at higher frequencies of the acoustic signal because signal excitation is higher at these higher frequencies. A theoretical model is then used to correct the formation shear slowness. However, such theoretical models require the correct wellbore diameter, wellbore fluid properties, measured formation slowness and the tool properties as an input, making the process complicated and burdensome. It is therefore desirable to develop a method and system for effective estimation of formation properties using acoustic array processing.
The disclosure may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the disclosure being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.